Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A system for generating a personalized user interface, the system comprising: a memory comprising machine-readable instructions, the machine-readable instructions comprising a software application having a user interface, and a personalization software tool programmed to monitor usage of the software application by a user, the user interface comprising a plurality of elements; and a processor configured to access and execute the machine-readable instructions, the personalization software tool being programmed to: (a) collect user usage information relating to the use of the software application by the user, the user usage information comprising one or more parameters, each parameter characterizing at least one of frequency of use of each of the plurality of elements, a pattern of usage of each the plurality of elements, and a relation of usage of each element to other elements of the plurality of elements; (b) identify categories of the plurality of elements, wherein each of the one or more elements of the plurality of elements are assigned to a respective category; (c) select a first category and identify each element of the selected category among the plurality of elements; (d) assign a weight to the one or more parameters for each element of the selected category among the plurality of elements; (e) rank each of the one or more elements of the plurality of elements of the user interface within its assigned category based on the one or more parameters and respectively assigned weight; (f) identify a first subset of the selected category corresponding to top-ranked elements among the plurality of elements in response to ranking of each of the plurality of elements; (g) display the top-ranked elements of the plurality of elements on the user interface according to the ranking based on the one or more parameters; (h) re-rank a second subset of the selected category corresponding to remaining elements of the selected category based on global user usage information relating to the use of the software application by a plurality of users, the global user usage information characterizing a usage of each of the second subset of the selected category by the user on the user interface; (i) display the remaining elements of the selected category on the user interface according to the re-ranking based on the global user usage information; (j) after displaying all elements of the selected category, determine whether other categories of elements that have not been selected remain; (k) repeat steps (a) to (i) when the other categories of elements that have not been selected remain; and (l) after displaying all elements of the other categories of elements, report personalized information for all categories to all available user interfaces.
2. The system for generating the personalized user interface of claim 1 , wherein the plurality elements of the user interface correspond to at least one of a plurality of icons, a plurality of radio buttons, a plurality of check boxes, a plurality of menus, a plurality of menu choices, and a plurality of text boxes.
A system generates a personalized user interface by dynamically selecting and arranging interface elements based on user-specific data. The system identifies user preferences, behaviors, or contextual information to determine which elements should be displayed and how they should be organized. The user interface elements include icons, radio buttons, checkboxes, menus, menu choices, and text boxes. These elements are presented in a layout tailored to the user, improving usability and efficiency by reducing unnecessary or irrelevant options. The system may also adapt the interface in real-time as user interactions or environmental conditions change. This approach enhances user experience by providing a more intuitive and relevant interface compared to static, one-size-fits-all designs. The system can be applied in software applications, websites, or any digital interface where customization improves functionality.
3. The system for generating the personalized user interface of claim 1 , wherein the user interface is a text console, and the plurality elements correspond to at least one of a plurality of commands, a plurality of options, and a plurality of files.
A system generates a personalized user interface for a text console, where the interface is customized based on user behavior and preferences. The system monitors user interactions with the console, such as command usage, option selections, and file access patterns, to identify frequently used elements. These elements are then prioritized or highlighted in the interface to improve efficiency. The personalized interface may include commands, options, or files that are most relevant to the user, reducing the need to navigate through less frequently used elements. The system dynamically adjusts the interface layout or presentation to reflect changes in user behavior over time. This approach enhances usability by reducing cognitive load and speeding up task completion for users working in text-based environments. The system may also support multiple users, tailoring each interface to individual preferences while maintaining a consistent underlying command structure. The goal is to optimize interaction efficiency in text consoles by adapting the interface to the user's workflow.
4. The system for generating the personalized user interface of claim 1 , further comprising one of a server and client device, the server or the client device comprising the memory and the processor.
A system generates a personalized user interface by analyzing user behavior data to determine user preferences and habits. The system includes a memory storing user behavior data and a processor configured to process this data to identify patterns and preferences. Based on these patterns, the system dynamically adjusts the user interface to prioritize frequently used features, customize layouts, or suggest relevant content. The system may operate on a server or a client device, where the server or client device includes the memory and processor components. The personalized user interface enhances user experience by reducing navigation time and improving accessibility to preferred functions. The system may also adapt in real-time as new user behavior data is collected, ensuring continuous optimization of the interface. This approach is particularly useful in applications where user efficiency and engagement are critical, such as productivity software, mobile apps, or enterprise systems. The system may further integrate with additional data sources, such as user feedback or external analytics, to refine personalization further. By leveraging machine learning or statistical analysis, the system can predict user needs and proactively adjust the interface to meet those needs. The overall goal is to create a seamless, intuitive, and adaptive user experience tailored to individual users.
5. The system for generating the personalized user interface of claim 1 , wherein the personalization software tool is configured to store in the memory the collected user usage information as part of a personalization database, the personalization database comprising the global user usage information.
A system generates a personalized user interface by analyzing user interactions with a software application. The system collects user usage information, such as navigation patterns, feature preferences, and interaction frequency, to tailor the interface dynamically. A personalization software tool processes this data to adapt the interface layout, content, and functionality to individual user needs. The tool stores the collected usage information in a memory as part of a personalization database. This database includes global user usage information, aggregating data from multiple users to identify broader trends and common preferences. The system then applies these insights to refine the interface for each user, improving efficiency and usability. The personalization process may involve machine learning algorithms to predict user behavior and adjust the interface proactively. By continuously updating the database with new usage data, the system ensures the interface remains optimized over time. This approach enhances user experience by reducing cognitive load and streamlining access to frequently used features. The system may also allow users to override or adjust personalization settings to better suit their preferences.
6. The system for generating the personalized user interface of claim 5 , wherein the plurality of users share a common relation, and the common relation is at least one of a workplace, an employer, and a license to the software application.
This invention relates to a system for generating personalized user interfaces based on shared relationships among users. The system identifies groups of users who share a common relation, such as a workplace, employer, or software license, and customizes the user interface for each group based on their shared attributes. The system analyzes user behavior, preferences, and interactions within the shared context to determine optimal interface configurations, such as layout, features, and accessibility settings. By tailoring the interface to the group's collective needs, the system enhances usability, productivity, and engagement. The system may also adapt dynamically as new users join or existing users modify their behavior. This approach ensures that users with similar roles or environments receive a streamlined and relevant interface, reducing the need for individual customization while maintaining efficiency. The system may integrate with existing software applications to apply these personalized interfaces across multiple platforms, improving consistency and user experience.
7. The system for generating the personalized user interface of claim 5 , wherein the one or more parameters correspond to a plurality of parameters, each parameter of the plurality of parameters being associated with a respective significance value characterizing a relevance of a given parameter for ranking of each of the plurality of elements of the user interface.
A system generates a personalized user interface by dynamically ranking and displaying elements based on user-specific parameters. The system addresses the challenge of presenting relevant content in a user interface by assigning significance values to multiple parameters, each reflecting the importance of a given parameter in determining the ranking of interface elements. These parameters may include user preferences, behavior patterns, or contextual data. The system evaluates each parameter's relevance to rank elements, ensuring the most pertinent information is prioritized in the interface. This adaptive approach enhances user experience by tailoring the interface to individual needs, improving efficiency and engagement. The system may integrate with other components, such as data collection modules or machine learning algorithms, to refine parameter significance over time. By dynamically adjusting the interface based on weighted parameters, the system provides a more intuitive and personalized interaction for users.
8. The system for generating the personalized user interface of claim 1 , wherein the one or more parameters characterize a method of usage of each of the plurality of elements, the method of usage including one of a mouse click and a keyboard click.
A system generates a personalized user interface by analyzing user interactions with interface elements. The system tracks how users engage with various elements, such as buttons, menus, or input fields, through specific input methods like mouse clicks or keyboard clicks. By characterizing these interactions, the system adapts the interface layout, appearance, or functionality to optimize usability based on individual preferences or behavior patterns. The system may also adjust the interface in real-time as the user continues to interact, ensuring continuous personalization. This approach improves efficiency and user experience by tailoring the interface to the user's natural interaction habits, reducing the need for manual adjustments or learning curves. The system can be applied in software applications, websites, or any digital interface where user engagement is critical. The underlying method involves collecting interaction data, analyzing usage patterns, and dynamically modifying the interface to reflect those patterns, enhancing accessibility and productivity.
9. The system for generating the personalized user interface of claim 1 , wherein the personalization software tool is programmed to rank each of the plurality of elements of the user interface based on a plurality parameters that include the one or more parameters.
A system generates a personalized user interface by dynamically adjusting its elements based on user-specific data. The system includes a personalization software tool that analyzes user behavior, preferences, and contextual factors to modify the interface elements, such as layout, content, and functionality. The tool ranks each element of the user interface according to multiple parameters, including user interaction history, task relevance, and environmental conditions. This ranking determines the prominence, visibility, or accessibility of each element, ensuring the interface adapts to individual needs. The system may also incorporate machine learning to refine personalization over time, improving efficiency and user satisfaction. The goal is to optimize the interface for productivity, accessibility, and user experience by tailoring it to the specific requirements of each user. The system can be applied in software applications, web interfaces, or digital platforms where customization enhances usability.
10. The system for generating the personalized user interface of claim 1 , wherein the personalization software tool is programmed to provide the user usage information using at least one machine learning technique.
A system generates a personalized user interface by analyzing user behavior and preferences to customize the interface layout, content, and functionality. The system includes a personalization software tool that collects and processes user interaction data, such as navigation patterns, feature usage, and time spent on different elements. This data is used to adapt the interface dynamically, improving usability and efficiency. The personalization software tool employs machine learning techniques to analyze the user usage information, enabling the system to predict user preferences and optimize the interface accordingly. The machine learning techniques may include supervised learning, unsupervised learning, or reinforcement learning, depending on the available data and the desired level of personalization. By continuously learning from user interactions, the system refines its recommendations and adjustments, ensuring the interface remains relevant and intuitive over time. This approach enhances user experience by reducing cognitive load and increasing productivity, particularly in complex or frequently used applications. The system may be applied in various domains, including software applications, websites, and digital platforms, where user engagement and satisfaction are critical.
11. The system for generating the personalized user interface of claim 1 , wherein each parameter of the one or more parameters is associated with a respective significance value characterizing a relevance of a given parameter for ranking of each of the plurality of elements of the user interface, and wherein the relevance of the given parameter is determined based on one of a particular project or task being performed via the software application by the user, a type of user, and a user group associated with the user.
A system generates a personalized user interface by dynamically ranking and displaying elements based on their relevance to a user. The system assigns significance values to parameters that influence the ranking of interface elements, where each parameter's relevance is determined by factors such as the specific project or task the user is engaged in, the user's type (e.g., role or expertise level), or the user group they belong to. These parameters may include user behavior, preferences, historical data, or contextual information. The system adjusts the interface layout, visibility, or prioritization of elements in real-time to enhance usability and efficiency. For example, a user working on a design project may see design tools ranked higher, while an administrative user may see project management features prioritized. The system may also adapt based on user feedback or performance metrics to refine parameter significance over time. This approach ensures the interface remains tailored to the user's current needs, reducing cognitive load and improving productivity.
12. The system for generating the personalized user interface of claim 1 , wherein display the top-ranked elements on the user interface comprises: identifying a first element of the top-ranked elements having a higher ranking than a second element of the top-ranked elements; and displaying the first element in a more prominent location of the user interface than the second element.
A system generates a personalized user interface by ranking and displaying elements based on user preferences or behavior. The system identifies a first element with a higher ranking than a second element among the top-ranked elements. The first element is then displayed in a more prominent location on the user interface compared to the second element. This ensures that higher-ranked elements are more visible or accessible to the user, improving usability and relevance. The ranking may be based on factors such as user interaction history, frequency of use, or explicit preferences. The system dynamically adjusts the interface layout to prioritize elements that are most important or frequently used by the individual user, enhancing efficiency and personalization. This approach is particularly useful in applications where users interact with multiple elements, such as dashboards, menus, or content feeds, where prioritizing relevant elements improves user experience. The system may also adapt over time as user behavior or preferences change, ensuring the interface remains optimized for the user's needs.
13. The system for generating the personalized user interface of claim 1 , wherein display the top-ranked elements on the user interface comprises: identifying a first element of the top-ranked elements having a lower ranking than a second element of the top-ranked elements; and displaying the first element in a less prominent location of the user interface than the second element.
A system generates a personalized user interface by ranking and displaying elements based on user preferences or behavior. The system identifies a first element among the top-ranked elements that has a lower ranking than a second element. The first element is then displayed in a less prominent location on the user interface compared to the second element. This ensures that higher-ranked elements are more visible, improving user experience by prioritizing relevant content. The ranking may be based on factors such as user interaction history, explicit preferences, or contextual relevance. The system dynamically adjusts the display to reflect these rankings, enhancing usability and engagement. The approach helps users quickly access the most important or frequently used elements while still providing access to lower-ranked items in a less prominent area. This method optimizes interface design by balancing visibility and accessibility of different elements.
14. The system for generating the personalized user interface of claim 1 , wherein the user interface is a first user interface and the plurality of elements is a first set of a plurality of elements, the software application comprising a second user interface comprising a second set of a plurality of elements, wherein the personalization software tool is programmed to: generate personalized ranking information characterizing a ranking of the top-ranked elements among the plurality of elements for the first user interface; and display the the second set of the plurality of elements on the second user interface based on the personalized ranking information.
A system generates personalized user interfaces for software applications by analyzing user behavior to rank interface elements. The system includes a personalization software tool that monitors user interactions with a first user interface, such as clicks, dwell time, or navigation patterns, to determine which elements are most frequently or effectively used. The tool then generates personalized ranking information that identifies the top-ranked elements for that user. This ranking is applied to a second user interface within the same application, where the tool displays elements from a second set based on the personalized ranking. For example, if a user frequently accesses certain features in the first interface, those features may be prioritized or prominently displayed in the second interface. The system dynamically adjusts the presentation of elements across different interfaces to improve usability and efficiency by tailoring the layout to individual user preferences and behaviors. This approach enhances user experience by reducing search time and increasing accessibility to frequently used functions.
15. The system for generating the personalized user interface of claim 1 , wherein the global user usage information is stored in a personalization database, the personalization database comprising respective global user usage information relating to a use of a given software application of a plurality of different software applications by a respective group of users, wherein a given group of users of the respective group of users corresponds to the plurality of users.
A system generates personalized user interfaces by leveraging global user usage data stored in a personalization database. The database contains usage information for multiple software applications, where each application's data is associated with a group of users who have interacted with it. The system analyzes this aggregated usage data to identify patterns, preferences, and behaviors across the user base. By correlating these insights with a specific user's individual usage history, the system dynamically customizes the user interface to enhance usability, efficiency, and engagement. The personalization database ensures that the system can adapt interfaces across different applications, tailoring them to the collective habits of similar user groups. This approach improves user experience by reducing learning curves and optimizing workflows based on proven usage trends. The system may also update the database in real-time as new usage data is collected, ensuring continuous refinement of the personalized interfaces. The solution addresses the challenge of creating intuitive, adaptive interfaces that cater to diverse user needs without requiring manual configuration.
16. The system for generating the personalized user interface of claim 15 , wherein the user has a relationship with the given group of users, the relationship comprising one of being affiliated with a similar company, working in a same technical field and operating under a particular type of license.
A system generates a personalized user interface for a user based on their relationship with a group of users. The relationship is defined by shared attributes such as affiliation with a similar company, working in the same technical field, or operating under a particular type of license. The system analyzes these relationships to customize the user interface, ensuring it aligns with the user's professional or organizational context. This personalization may include tailored layouts, relevant tools, or content recommendations that reflect the user's shared characteristics with the group. The system dynamically adjusts the interface to enhance usability and relevance, improving efficiency and engagement for users within the defined relationship. By leveraging these shared attributes, the system provides a more intuitive and context-aware experience, reducing the need for manual customization and streamlining workflows. The approach ensures that users with similar professional backgrounds or affiliations receive an interface optimized for their specific needs, enhancing productivity and collaboration.
17. A method for generating a personalized user interface, the method comprising: (a) monitoring a software application being used by a user to collect user usage information relating to a use of the software application that includes a user interface comprising a plurality of elements, the user usage information comprising one or more parameters, each parameter characterizing at least one of frequency of use of each of the plurality of elements, a pattern of usage of each the plurality of elements, and a relation of usage of each element to other elements of the plurality of elements; (b) identifying categories of the plurality of elements, wherein each of the one or more elements of the plurality of elements are assigned to a respective category; (c) selecting a first category and identifying each element of the selected category among the plurality of elements; (d) assigning a weight to the one or more parameters for each element of the selected category among the plurality of elements; (e) ranking each of the one or more elements of the plurality of elements of the user interface within its assigned category based on the one or more parameters and respectively assigned weight to identify a first subset of the selected category corresponding to top-ranked elements among the plurality of elements; (f) displaying the top-ranked elements of the plurality of elements on the user interface according to the ranking based on the one or more parameters; (g) re-ranking a second subset of the selected category corresponding to remaining elements of the selected category based on global user usage information relating to the use of the software application by a plurality of users, the global user usage information characterizing a usage of each of the second subset of the selected category by the user on the user interface; (h) displaying the non-top ranked elements of the plurality of elements on the user interface according to the re-ranking based on the global user usage information; (i) determining whether other categories of elements that have not been selected remain in response to displaying all elements of the selected category; (j) repeating steps (a) to (h) when the other categories of elements that have not been selected remain; and (k) reporting personalized information for all categories to all available user interfaces in response to displaying all elements of the other categories of elements.
The method involves generating a personalized user interface by analyzing user behavior within a software application. The system monitors how a user interacts with the application's interface elements, tracking metrics such as frequency of use, usage patterns, and relationships between elements. These elements are categorized, and within each category, individual elements are ranked based on weighted parameters derived from the user's behavior. The top-ranked elements are displayed prominently, while lower-ranked elements are re-ranked using global usage data from multiple users. This ensures that less frequently used or less relevant elements are still accessible but prioritized based on broader usage trends. The process repeats for all categories until all interface elements are personalized and displayed across available user interfaces. The method dynamically adapts the interface to individual user preferences while incorporating insights from collective usage patterns, enhancing usability and efficiency.
18. The method for generating the personalized user interface of claim 17 , wherein the user interface is a first user interface and the plurality of elements is a first set of a plurality of elements, the software application comprising a second user interface comprising a second set of a plurality of elements, the method further comprising: generating personalized ranking information characterizing a ranking of the top-ranked elements among the plurality of elements for the first user interface; and displaying the second set of the plurality of elements of the second user interface based on the personalized ranking information.
This invention relates to personalized user interfaces in software applications, specifically addressing the challenge of dynamically adapting interface elements based on user preferences or behavior. The method involves generating a personalized ranking of elements within a first user interface, where these elements are prioritized according to user-specific criteria such as usage frequency, relevance, or interaction history. The ranked elements are then used to influence the display of a second user interface within the same application. The second user interface presents its own set of elements, but their arrangement or visibility is adjusted based on the personalized ranking derived from the first interface. This ensures consistency in user experience across different interfaces of the application, improving usability and efficiency by prioritizing elements that are most relevant to the individual user. The approach leverages user data to dynamically tailor interfaces, enhancing engagement and reducing cognitive load by minimizing irrelevant or less frequently used elements. The method applies to any software application with multiple interfaces, such as productivity tools, mobile apps, or enterprise systems, where personalized content presentation is beneficial.
19. The method for generating the personalized user interface of claim 17 , wherein the one or more parameters correspond to a plurality of parameters, each parameter of the plurality of parameters being associated with a respective significance value characterizing a relevance of a given parameter for ranking of each of the plurality of elements of the user interface, and wherein the relevance of the given parameter is determined based on one of a particular project or task being performed via the software application by the user, a type of user and a user group associated with the user.
This invention relates to personalized user interfaces in software applications, specifically methods for dynamically adjusting interface elements based on user-specific parameters. The problem addressed is the inefficiency of static user interfaces that do not adapt to individual user needs, project contexts, or user roles, leading to reduced productivity and usability. The method involves generating a personalized user interface by analyzing multiple parameters associated with the user, such as the specific project or task being performed, the user's type (e.g., role or expertise level), and the user group they belong to. Each parameter is assigned a significance value that quantifies its relevance in determining the ranking or prioritization of interface elements. For example, a parameter like "project type" may have a high significance value when ranking tools or features relevant to that project, while a "user role" parameter may prioritize administrative functions for managers versus creative tools for designers. The system dynamically adjusts the interface layout, visibility, or ordering of elements based on these weighted parameters, ensuring the most relevant features are prominently displayed. This approach enhances user experience by tailoring the interface to the current context, improving efficiency and reducing cognitive load.
20. The method for generating the personalized user interface of claim 17 , wherein the user has a relationship with the plurality of users, the relationship comprising one of being affiliated with a similar company, working in a same technical field and operating under a particular type of license.
This invention relates to personalized user interfaces in collaborative or professional environments, addressing the challenge of tailoring interfaces to users based on their relationships with others. The method generates a personalized user interface by analyzing a user's relationships with a group of users, where these relationships are defined by shared affiliations, such as working at the same company, operating in the same technical field, or holding a particular type of license. The system identifies these relationships to customize the interface, ensuring that the user's experience aligns with their professional or collaborative context. This may involve adjusting displayed content, tools, or features to reflect shared interests, access levels, or workflows among connected users. The approach enhances usability and efficiency by dynamically adapting the interface to the user's network, reducing the need for manual customization and improving collaboration. The method leverages relationship data to provide a more intuitive and relevant interface, particularly in environments where shared context is critical.
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December 1, 2020
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